Version 0.13.0

Since publication, I made a few minor bug fixes based on the feedback, including:

[1] Windows user's feedback on path delimiter difference
[2] some newly added argument in preprocessing module

main functionalities remain intact, but the update will help the wide usage for other convenient functions

Zenodo citable version

This is a release to create a zenodo citable version to be compliant with the journal's publishing requirement and increase reproducibility

Version 0.12.0

In this new release:

1. Adding sctriangulate.spatial module
2. Adding different mode for computing annotation importance including ranking-based method
3. Adding elo_rating for computing the overall quality score for each annotation
4. Adding logger module for proper and clean logging
5. streamlined the API to make it easy to understand and run, no need to dig into low-level implementation
6. flexibly adding new metrics and callable
7. Allowing specifying number of cores to use
8. fix bugs in the code and doc

v0.10.1

Feature Enhancement:

1. Neighborhood Components Analysis (supervised PCA embedding)

2. Coexpression plot

3. Sankey plot

4. Now supports for single-cell splicing data and single-cell mutation data multimodal analysis

5. Can visualize as many as 433 single cell clusters

6. color module support colorful stdout

polish the documentation and fix bugs

scTriangulate_0.9.2

This version is mainly for feature enhancement:

Add build_custom_continuous_cmap and build_custom_divergent_cmap functions in the colors module.

scTriangulate_0.9.1

Version 0.9.1 2021/10/10

1. Add the option for whether assessing the raw cluster or not.
2. Polish the documentation and fix some typos

scTriangulate_0.9.0

First public release

scTriangulate_v0.8.0

In this new release:

1. a ready-to-use python package
2. can generate publication-quality figure
3. passed all the test functions
4. make sure all the default argument values are correct

scTriangulate_0.7

In this new version:

1. better inspection visualization
2. add 7 modes to exclude artifact genes
3. filter genes for the heatmap visualization

scTriangulate_0.6.1

First ready version, you can run the tool through the command line.

Four modes:

metrics
shapley
combine
cluster